code: def rfecv_quick_method(image="rfecv_quick_method.png"):
      X, y = load_credit()
  
      _, ax = plt.subplots()
      cv = StratifiedKFold(5)
      visualizer = rfecv(
          RandomForestClassifier(),
          X=X,
          y=y,
          ax=ax,
          cv=cv,
          scoring="f1_weighted",
      )
      visualizer.show(outpath=os.path.join(IMAGES, image))
  
file_path: yellowbrick/docs/api/model_selection/rfecv.py
imports: import os
  import matplotlib.pyplot
  from sklearn.svm import SVC
  from sklearn.datasets import make_classification
  from sklearn.ensemble import RandomForestClassifier
  from sklearn.model_selection import StratifiedKFold
  from yellowbrick.model_selection import RFECV, rfecv
  from yellowbrick.datasets import load_credit
label_desc: Use image node_id 3 for calling a global function with example usage: rfecv_quick_method(image) without return types